JP5671285B2 - Method and system for demand response in a distribution network - Google Patents

Method and system for demand response in a distribution network Download PDF

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JP5671285B2
JP5671285B2 JP2010202527A JP2010202527A JP5671285B2 JP 5671285 B2 JP5671285 B2 JP 5671285B2 JP 2010202527 A JP2010202527 A JP 2010202527A JP 2010202527 A JP2010202527 A JP 2010202527A JP 5671285 B2 JP5671285 B2 JP 5671285B2
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load
facility
participating user
response
limit
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JP2011062075A (en
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ラジェシュ・チャギ
ジェイソン・ウェイン・ブラック
ロナルド・レイ・ラーソン
アウグスト・レイモン・セルホーン
シャオフェン・ワン
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ゼネラル・エレクトリック・カンパニイ
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/0006Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network for single frequency AC networks
    • H02J13/0013Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network for single frequency AC networks characterised by transmission structure between the control or monitoring unit and the controlled or monitored unit
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02BCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/32End-user application control systems
    • Y02B70/3208End-user application control systems characterised by the aim of the control
    • Y02B70/3225Demand response systems, e.g. load shedding, peak shaving
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02BCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B90/00Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02B90/20Systems integrating technologies related to power network operation and communication or information technologies mediating in the improvement of the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as enabling technology in buildings sector
    • Y02B90/26Communication technology specific aspects
    • Y02B90/2607Communication technology specific aspects characterised by data transport means between the monitoring, controlling or managing units and the monitored, controlled or operated electrical equipment
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00Systems supporting the management or operation of end-user stationary applications, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y04S20/20End-user application control systems
    • Y04S20/22End-user application control systems characterised by the aim of the control
    • Y04S20/222Demand response systems, e.g. load shedding, peak shaving
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S40/00Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
    • Y04S40/10Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by communication technology
    • Y04S40/12Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by communication technology characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10TTECHNICAL SUBJECTS COVERED BY FORMER US CLASSIFICATION
    • Y10T307/00Electrical transmission or interconnection systems
    • Y10T307/25Plural load circuit systems
    • Y10T307/406Control of current or power
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10TTECHNICAL SUBJECTS COVERED BY FORMER US CLASSIFICATION
    • Y10T307/00Electrical transmission or interconnection systems
    • Y10T307/25Plural load circuit systems
    • Y10T307/406Control of current or power
    • Y10T307/414Load current proportioning or dividing
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10TTECHNICAL SUBJECTS COVERED BY FORMER US CLASSIFICATION
    • Y10T307/00Electrical transmission or interconnection systems
    • Y10T307/25Plural load circuit systems
    • Y10T307/406Control of current or power
    • Y10T307/422Constant magnitude control
    • Y10T307/43By control of one or more load circuits
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10TTECHNICAL SUBJECTS COVERED BY FORMER US CLASSIFICATION
    • Y10T307/00Electrical transmission or interconnection systems
    • Y10T307/25Plural load circuit systems
    • Y10T307/461Selectively connected or controlled load circuits
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10TTECHNICAL SUBJECTS COVERED BY FORMER US CLASSIFICATION
    • Y10T307/00Electrical transmission or interconnection systems
    • Y10T307/25Plural load circuit systems
    • Y10T307/461Selectively connected or controlled load circuits
    • Y10T307/469Condition responsive
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10TTECHNICAL SUBJECTS COVERED BY FORMER US CLASSIFICATION
    • Y10T307/00Electrical transmission or interconnection systems
    • Y10T307/25Plural load circuit systems
    • Y10T307/461Selectively connected or controlled load circuits
    • Y10T307/484Sequential or alternating

Description

  System reliability is very important for distribution networks such as public services. Load variability is an important factor that impairs system reliability. Public services maintain models and techniques for load forecasting, but the actual system load is variable and constantly changing. There are a limited number of ways that public services can be used to respond to load changes or system emergencies. This is especially true at the distribution level. Methods for responding to power distribution emergencies usually involve opening the circuit, which leads to indiscriminate load limiting.

  A demand response solution is available that reduces energy demand in response to peak load conditions. Responding to emergency situations in the power system using demand-side resources is usually limited to batch load limiting schemes (eg, planned power outages). More specifically, collective load limiting and / or voltage reduction (lighting limitation) are current methods of handling overloaded circuits or transformers at the distribution level. Either method has a significant impact on all users in the region concerned. There is a limited demand response program for large corporations and business users who are willing to reduce the load if there is a prior notice to alleviate overload conditions, but these programs are not suitable for distribution level failures. It is common to be able to react to power level failures rather than.

  Demand response solutions for distribution level emergencies, especially in residential areas, are difficult to manage because the network structure changes dynamically. As a result, it becomes difficult to identify users who can respond to a particular emergency. Public services have provided some users with direct control devices for certain loads, such as heating and cooling devices, pool pumps, etc., but public services can provide these devices for specific network needs. As such, it cannot be managed efficiently and effectively through the power distribution network.

  For these and other reasons, the present invention is necessary.

US Patent Application Publication No. 2009/0200867

  A method and system for controlling a load in a public service distribution network is provided, the method and system being a facility associated with a node participating in a demand response program to reduce the load at the node to a desired level. By selecting, a restriction event is initiated for the nodes in the distribution network. More specifically, the present system and method allows the selection of only enough participating facilities associated with a node that are necessary to reduce the load to a desired level.

  The nature and various additional features of the present invention will become more apparent upon review of exemplary embodiments of the invention that are schematically illustrated in the drawings. The same reference number represents the matching part.

It is a figure which shows the demand reaction system by one Embodiment of this invention. FIG. 2 is a flow diagram illustrating a demand response control process associated with the demand response control system shown in FIG. 1 according to one embodiment of the invention. It is a flowchart which shows the facility reaction estimation process by one Embodiment of this invention. 6 is a graph illustrating facility reaction scheduling according to an embodiment of the present invention. It is a flowchart which shows the plant | facility selection process by one Embodiment of this invention.

  Although the above-identified drawings illustrate alternative embodiments, other embodiments of the invention are also contemplated, as discussed in the discussion. In all cases, this disclosure presents illustrated embodiments of the present invention by way of representation and not limitation. Many other modifications and embodiments can be devised by those skilled in the art which are within the scope and spirit of the principles of the present invention.

  Embodiments described herein are directed to demand response methods and systems that enable the use of residential load resources to control loads and respond to emergencies in a power distribution network. The emergency response according to embodiments of the present invention expands the range of emergencies that can be mitigated by demand response and replaces the targeted load demand program with non-critical load restrictions. Allow reaction. This solution is targeted in that it allows implementation at any node in the network, with minimal impact on limits and minimal impact / cost burden to eliminate a given emergency. Is selective in that Although embodiments of the present invention are described in the context of responding to emergencies in a power distribution network, the method and system can be used for other purposes such as general load control for energy savings, or peak shaving or reduction programs, for example. Those skilled in the art will appreciate that the present invention can also be used for these purposes.

  As used herein, the term “node” includes, but is not limited to, transformers and substations, any distribution network in which two or more users or two or more facilities are electrically connected. The point of.

  As used herein, the term “module” refers to software, hardware, or firmware, or any combination thereof, that implements or facilitates any system, process, or process described herein. Also refers to the functionality to do.

  Targeted load limiting according to embodiments of the present invention allows a public service to select a particular node that initiates a limiting event so that the load on an unloaded circuit is not affected. Selective restrictions include optimizing how many loads are restricted and which specific facilities / devices are restricted so as to minimize the impact on users in the network. When a particular node (s) is targeted, the selective limit determines the minimum load amount that can be limited to eliminate overload and distributes only that amount. Selective restrictions also ensure that non-hazardous / minimum cost loads are limited prior to any critical loads. Targeted selective load limiting may be actively used to handle emergency situations during power distribution, such as overload.

  Embodiments of the present invention include load rebound estimation, load limit aggregation, and facility selection. Facility selection restores stability to the grid while minimizing impact on load and maintaining hazardous loads. The load limiter in the facility is a water heater, pool pump, air conditioner, etc., and other devices that maintain a dangerous load while allowing short-term load limits that have little impact on the quality of life, such as lighting and electronic devices. Including any device.

  An exemplary demand response system according to an embodiment of the invention is shown in FIG. The system 100 includes a public service control center 110 and a facility or public service user 112. Each facility includes a utility meter 114 that measures public service usage from the load 116 at the facility. The instrument 114 may be a “smart” instrument with a transceiver (not shown), known as an advanced meter reading infrastructure (AMI) 118 that communicates with the public service control center 110 together. Communication can be performed, for example, by WAN (eg, the Internet) 120, WiMAX, broadband, and / or power line carrier. Any suitable communication means may be used. To facilitate the description of embodiments of the present invention, one public service control center 110 and a limited number of public service users 112 are shown in FIG. However, it should be understood that embodiments of the present invention are not limited to such a number, and a public service may have any number of public service control centers and users within the distribution network.

  The public service control center 110 includes an energy management system (EMS) module 122 that performs load forecasting on the network, monitors, controls, and optimizes the performance of the power generation and transmission system. A supervisory control / data acquisition (SCADA) module 123 provides real-time information at different points in the grid and also performs local control. The power outage management system (OMS) module 124 monitors load status information and power outage recovery information regarding the facility 112 in the power distribution network. Some of the functions performed by the OMS module 124 include failure prediction, providing information about the extent of power outages and the impact on the user, and prioritizing recovery operations. The OMS module 124 operates based on a detailed network model of the power distribution system generated and maintained by the Geographic Information System (GIS) module 126. The power distribution management system (DMS) module 128 reacts to inconvenient or unstable network conditions in real time by providing information about load status and load response. The DMS module 128 manages responses to alarms and / or events. For example, user information including service contract information, participation in demand reaction programs, and contract price information is monitored and controlled by a user information system (CIS) module 130. The billing operation for the user is performed by the billing module 132. The network management system (NMS) module 142 performs communication management and provisioning for the DR module 140 and the meter-reading device 114.

  The public service control center 110, for example, data such as historical data about each user or facility in the distribution network based on information from the EMS module 122, DMS module 128, SCADA module 123, DR module 140, and OMS module 124. Is also included. The historical data may include information about the user's public service usage, including, for example, load type, time of use (TOU), duration of use, limit or demand response event. User usage information stored in the data storage unit 134 includes load data including load per hour and price per hour for 24 hours, weather information (temperature, humidity, wind speed, heating and cooling temperature). In addition, it can be updated periodically (for example, every hour or every day) with environmental data including date and time information such as day of the week and season. Further, the data storage unit 134 stores event data related to each user. More specifically, the data storage unit 134 stores history information about whether the user has participated in the demand response event, start time and end time, day of the week, season, and the like. User interface module 136 provides information to an operator at public service control center 110 via, for example, display 138.

  The demand response (DR) module 140 in the public service control center 110 uses information from various modules in the public service control center 110 to use in the power distribution network, such as a network emergency requesting a load reduction. Respond to power demand events. According to an embodiment of the present invention, the DR module 140 reacts to an event by implementing a targeted selective load limit.

  Many public service users participate in the demand response program, where users are compensated for agreeing to load limits with immediate notice if necessary. The demand response process according to embodiments of the present invention optimizes the response to a load limit event only by accessing users in the identified area of interest who have agreed to participate in the load limit program. Users within the affected area are selected as needed and at the lowest cost so as to minimize the cost of the load limiting event. Load limiting is directly controlled by public services by switch switching or performed by the user. More specifically, load limiting can be used to remotely switch off a device (eg, an HVAC unit) that has been agreed to in a contract so that public services are directed within the CIS module 130, or to reduce the load at home. / Performed by direct or indirect load control so that load control signals can be sent to the building energy management (HEM) system. The HEM system can then determine which devices should be reduced to meet public service requirements. Load limiting to support emergency response can also be achieved through a dynamic pricing program, where users agree to variable pricing for a certain number of emergency events, depending on the price discount. To do. In response to the urgent price, the user decides how much load to reduce. Desired system level limits can be achieved by signaling an appropriate number of users based on the estimated price responsiveness of the users.

  The limit amount will depend on the equipment involved (eg, HVAC, water heater, etc.), control type (eg, on / off / setback), and the current status of the equipment (eg, running, out of service). . Compensation can have a fixed component for participation and a variable component based on the amount of restriction at each event. Further, the contract can specify the number of times a user can be required to participate in a load limit event, which can vary from user to user.

  FIG. 2 shows a flow diagram for a demand response process according to one embodiment of the present invention. The DR module 140 communicates with other modules in the public service control center 110, including the EMS module 122, the OMS module 124, the GIS module 126, the DMS module 128, the CIS module 130, and the user interface module 136. Information received from the various modules is used to determine a demand response in the demand response process 200. Process 200 may be initiated automatically or by a public service operator when notified that an overload situation has occurred or is likely to occur, as shown in step 210. This process may be initiated whenever a utility operator determines that a load limit event should be invoked and matches a user contract.

  When the process is initiated, in step 212, the DR module 140, for example, information identifying a node or region in the distribution network that encounters a demand for power that will exceed or will soon exceed available power, load Receive from the DMS module 128, the AMI 118, and the OMS module 124 the identification of the facilities associated with the nodes participating in the restriction program, the required load restrictions and the duration of the load restrictions required to react to the event. . Alternatively, the limit amount and limit period may be entered by an operator via the user interface 138 and the user interface module 136. At step 214, the process estimates a limiting response from each facility associated with the relevant node. More specifically, step 214 estimates the amount of load limit that can be provided by each facility associated with the node that is part of the load limit program. The limiting response applicable to each participating facility can be estimated from real-time data and / or historical data. The DR module 140 obtains real-time data from the HEM, instrument 114, EMS module 122, DMS module 128 or contract parameters. History data is obtained from the data storage unit 134. The estimated amount is aggregated at step 216 to determine the total amount of load limit that can be obtained from the participating facility associated with the node to react to the event.

  At step 218, the process then estimates the network response to the overload event based on the estimated aggregate load limit determined at step 216. This estimation is performed because some facilities may encounter communication / control failures associated with the network management system and may not receive DR signals. Therefore, the availability of aggregate reactions must be adjusted to reflect these failures. If the estimated aggregate response is greater than the network request at step 220, a restriction event is invoked and a facility is selected for load restriction at step 222. If the estimated aggregate response is less than the network demand at step 220, the call to the limit event for all participating facilities may not be sufficient to avoid an emergency situation of overload, and therefore, as shown in step 224, the limit event In addition to calling, we propose that additional responses to overload events must be considered.

  Comparing the estimated limiting response with the required limiting response, both the limiting amount (kW or MW) and duration must be satisfied to determine if the limiting response is sufficient. One decision method uses energy (the limit multiplied by the period) as a comparative measure. In this case, the required network energy is calculated and compared to the aggregate energy for all participating facilities. Since the network limit period may be different from the facility limit period allowed in individual facility contracts, the facility may need to be scheduled to limit the load at different times. Note that since power distribution systems typically provide three-phase power, facilities are assigned to one of the phases such that the total load is evenly distributed across each phase. Therefore, the time limit for the facility should be scheduled so that the load balance for all phases is maintained. This type of scheduling problem is often referred to as the knapsack problem in Operations Research literature. To quickly estimate whether the response is sufficient, slack factors can be used to reveal scheduling constraints. For example, it can be inferred that there is sufficient response if the aggregate facility energy is, for example, at least 120% of the energy required. The number may be greater or less than 120%, depending on the relative size of the facility limit compared to the required network limit.

  When a facility is selected at step 222, the DR module 140 initiates a load limit event at step 226 and the corresponding user is notified. More specifically, DR module 140 and DMS module 128 indicate that an event has started and send a signal identifying the event type, requested limit, start time, and duration to the selected facility. . The signal is sent using, for example, AMI 118 and NMS module 142. In addition to or instead of automatic initiation, the user can be notified by email or telephone. In some applications, a reception notification signal is supplied from the facility to the public service control center 110. At step 228, the actual network response to the selected facility's load limit is determined by information provided from the DMS module 128, the EMS module 122, or the SCADA module 123, and the OMS module 124. If the estimated network response is satisfied with the actual load limit of the selected facility, it is determined at step 230 whether the event is over (the limit period has been met). If the event is over, the alarm is cleared at step 232. If the event has not ended, the process returns to step 228. If it is determined at step 228 that the load limit for the selected user is greater than the network requirement, at step 234 one or more of the selected users are given a revocation notice. If it is determined at step 228 that the load limit for the selected facility is less than the network requirement, at step 236, an additional facility is selected. Increasing and decreasing the number of users selected may be done, for example, gradually or in any other suitable manner. In either case, the process returns to step 228 for continued monitoring until it is determined in step 230 that the event is over.

  The flow diagram of FIG. 3 illustrates a process for estimating the facility restriction response of participating users associated with a related node. Based on the information provided to the DR module 140 regarding the facilities associated with the node and participating in the load limiting program shown in step 300, steps 302-308 are performed for each associated facility. The process determines at step 302 whether a load limit is available from a HEM system that may be located at the facility. If this information is available from the HEM, at step 304, the data is applied as an estimated restriction response for the facility. If it is determined in step 302 that the facility does not include a HEM device, it is determined in step 306 whether historical data regarding the facility for the previous restricted event exists in the data storage unit 134. If it is determined that historical data about the facility is indeed present, at step 308, the historical data is applied as an estimated restriction response for that facility. If it is determined in step 306 that there is no historical data for the facility, in step 310, the estimated restriction response for the facility is based on historical data from a similar facility stored in the data storage unit 134 or stored in data. It is determined from a predetermined profile in the unit 134.

  Discuss in more detail the process of using historical data as an estimated limiting response to a facility. As described above, the status information regarding each facility is stored in the data storage unit 134. Since the frequency of data retrieval and storage is variable, any frequency suitable for the application may be set. In the discussion, the frequency of retrieval and storage is considered to be every day, ie every 24 hours. The DR module 140 retrieves data relating to the facility from the data storage unit 134. The DR module 140 determines which past day is most similar to today. More specifically, it is determined which day in the past corresponds most closely to today's usage time, day of the week, season, temperature, humidity and any other data that will affect the load. The If one or more similar days are found, it is determined whether a demand response event has occurred on any of these days. If similar days with demand response are found, the average response of those days can be used as a response estimate for the current load limit event.

  As an example, if today is noon on a summer Sunday, the DR module 140 searches for data corresponding to noon on a past summer Sunday. Module 140 also determines whether there are such days when the facility was part of a demand response event. If such a day is found, the load limiting response for that facility on that day is obtained and this amount is used as the estimated limiting response for that facility. If multiple similar days are found, the average load limit response is used as the estimated load limit response for the facility. To calculate responses using historically similar days where there was a demand response event on one day but not on the other, compare the data and identify the differences between the data for the facility It can be applied as an estimated limiting reaction.

  If a similar day with a demand response event is not found, the DR module 140 uses the data obtained from another day when the demand response event occurred and uses the response rate obtained from that day to the facility for the current event. Use as an estimated limiting response. In other words, if there is a past day that responded to a demand response event and the response was a 10 percent load limit, the 10 percent load limit value is determined under the current conditions and this value is used as the estimated limit response for the facility. use. Similarly, by using a plurality of past days with a demand response event and applying a regression technique to the load data obtained from those days, an estimated limited response to the facility can be given.

  Another estimation approach involves averaging the limiting responses from several different nearby facilities that are similar in size, number of rooms, floors, etc. The average limiting response can be used as an estimated limiting response for the target facility.

  Another approach involves estimating a limiting response using predetermined profile data. Profile data may include several standard profiles based on facility size, number of rooms, floors, etc., as well as typical limits for each facility under different conditions. During the estimation process, the DR module 140 selects the profile that most closely resembles the target facility and uses the corresponding limiting amount for the condition as the estimated limiting response for the facility.

  The facility selection process at step 222 of FIG. 2 is complicated by the fact that each facility may have a maximum limit and / or duration agreed upon in the user contract. The cost limit can vary from facility to facility. Furthermore, the user contract may limit the number of participations in the agreed demand response event. Maximum limits and durations can vary from facility to facility or user, so if the actual restricted event duration is longer than the restricted duration allowed by some facilities, or equals the restricted duration for other facilities, May be longer than the period. As shown in FIG. 4, in order to meet system-level limits and periods for nodes, facilities will generally be scheduled to limit loads at different times over different periods, resulting in a cumulative effect of It will meet the system level limiting requirements at the lowest cost while maintaining load balance across all three phases of the power distribution system.

  One goal for public services is to minimize the cost of responding to demand response events. Therefore, the facility selection process may be performed based on the lowest cost. The selection process can be formulated, for example, as a multidimensional knapsack problem studied in the operations research literature. There are many solutions to this problem, including mathematical programming, dynamic programming, and greedy algorithms, among others. For example, one approach is to use a greedy algorithm, where the selection begins at the lowest price and continues with replenishment or selection to obtain the required limit as shown along the y-axis in FIG. Then, further selection continues to meet the period requirements along the x-axis of FIG. In this process, some facilities may not need to be called throughout the contract limit period, i.e., only used for quantities that meet the algorithm to meet the limits and duration needs.

  FIG. 5 is a flow diagram further illustrating step 222 of selecting a facility for load limitation shown in FIG. In step 500, the selection process first retrieves the availability limit (kW) and duration (eg, minutes, hours) determined in step 214 of FIG. At step 502, the required and expected duration of network restrictions at the node (eg, minutes, hours) is retrieved. At step 504, the knapsack problem is formulated and solved using the facility selection techniques discussed above to select facilities to meet the restriction needs and duration. In step 506, this problem resolution provides a set of facilities that should be restricted to meet the required limits and duration at the node.

  Rebound effects are considered when estimating facility restriction responses. This effect refers to the phenomenon that in practice many types of demand will actually consume more than its “normal” state following a reduction or restriction event. This increase in subsequent intervals may be referred to as a “rebound effect”. When the facility reaction is estimated from the history data, the facility load on the same day with the restriction event is compared with the case without the restriction event. This difference automatically includes a rebound effect. The same is true for other sources that estimate restriction responses, including real-time estimation and profile estimation. For real-time estimation (eg, data is obtained from the HEM), the HEM must take load rebound into account when making a limit estimate. Similarly, since profiles are created from historical data, profile restrictions will also include rebounds in the profile.

  In the general description, an embodiment of a targeted selective demand response method and system has been disclosed that expands the range of emergencies that can be made by demand response and replaces non-hazardous load limitations with a batch load limitation program. Such embodiments allow targeting nodes in the distribution network that require demand response, by selecting facilities associated with the node and participating in a demand response program to reduce the load to an acceptable level. Can perform demand response. More specifically, the system and method can select only enough participating facilities associated with the nodes that are necessary to reduce the load to an acceptable level. In addition, the selected facility contributes to the lowest source impact / cost to resolve a given emergency.

  Although embodiments of the present invention are described in the context of responding to emergencies in a power distribution network, the methods and systems may be used for other purposes, such as general load control for energy savings, for example. Those skilled in the art will understand.

  While only certain features of the invention have been illustrated and described herein, many modifications and changes will occur to those skilled in the art. Accordingly, it is to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of this invention.

DESCRIPTION OF SYMBOLS 100 Demand reaction system 110 Public service control center 112 Public service user 114 Instrument 116 Load 116 Advanced meter reading infrastructure 120 Wide area network 122 Energy management system module 123 Monitoring control / data acquisition module 124 Power outage management system module 126 Geographic information system module 128 Power distribution management system module 130 User information system module 132 Request module 134 Data storage unit 136 User interface module 138 Display 140 Demand response module 142 Network management system module

Claims (10)

  1. A method for controlling a load on a distribution network of public service users, each of the users having a corresponding facility,
    Receiving, from the public service, information regarding nodes in the distribution network that require power above a predetermined threshold, the information reducing node identification information and the demand for power below the predetermined threshold A limit amount and a limit period required to do, and information identifying a participating user's facility associated with the node and participating in a load limiting program from the public service, and
    Estimating a load limiting response for the participating user facility;
    Estimating a load limiting response adjusted based on communication connectivity;
    Wherein the adjusted load shed response, compared to the required said limit amount and the restriction period the power demand to reduce to less than the predetermined threshold, determining a node response to the adjusted load shed response And steps to
    Initiating a load limit event when the node response is sufficient to reduce the power demand below the predetermined threshold;
    Selecting one or more of the participating user facilities for the load limiting event based on the node response;
    Including methods.
  2.   The method of claim 1, wherein the step of estimating the load limiting response further comprises estimating a rebound effect on the participant user facility.
  3. Informing the one or more participating user facilities of the load limiting event;
    Comparing an actual node response to the node response for the one or more participating user facilities;
    Adjusting the one or more participating user facilities selected for the load limiting event based on the comparison;
    The method according to claim 1, further comprising:
  4. Said step of adjusting comprises:
    Increasing the number of participating user facilities when the actual node response is less than the node response;
    Reducing the number of participating user facilities when the actual node response is greater than the node response;
    The method of claim 3 comprising:
  5. The step of estimating the load limiting response of the participating user facility is, for each of the participating user facilities, load limiting data from one of the devices located at the participating user facility, the participating user; 5. A method according to any of claims 1 to 4, comprising the step of obtaining a load limit history profile for a facility, a load limit history profile for another participating user facility, or a predefined facility profile.
  6.   The step of obtaining the load restriction data from the device located at the participating user facility includes the step of obtaining the load restriction data from a home energy management system located at the participating user facility. Item 6. The method according to Item 5.
  7. The step of obtaining the load restriction data from the load restriction history profile relating to the participating user facility,
    Comparing current load limit condition data with historical load limit condition data in the load limit history profile for the participating user facility;
    Identifying a previous load limit event that most closely matches the current load limit condition for the limit event;
    Retrieving a past load limit reaction for the previous load limit event;
    Applying the past load limit reaction as the load limit data;
    The method of claim 5 comprising:
  8. Obtaining the load limit data from the load limit history profile for another participating user facility;
    Comparing a participating user facility profile for the participating user facility with other participating user facility profiles;
    Identifying different participating user facility profiles that most closely match the participating user facility profiles;
    Comparing current load limit condition data for the participating user facility with historical load limit condition data in a load limit history profile for the different participating user facilities;
    Identifying a previous load limit event for the different participating user facilities that most closely matches the current load limit condition data for the limit event;
    Retrieving a past load limit response for the previous load limit event for the different participating user facilities;
    Applying the past load limit response for the different participating user facilities as the load limit;
    The method of claim 5 comprising:
  9. The step of obtaining the load limit data from the predefined facility profile comprises:
    Comparing the participant user facility profile for the participant user facility with a predefined facility profile;
    Identifying the predefined facility profile that most closely matches the participating user facility profile;
    Retrieving profile load limit data for the predefined facility profile;
    Applying the profile load limit data relating to the predefined facility profile as the load limit data;
    The method of claim 5 comprising:
  10. The step of selecting the one or more of the participating user facilities for the load limiting event determines a set of participating user facilities to select for the load limiting event using an operations research method. The method according to claim 1, comprising the step of:
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